Based on our record, AWS Lambda seems to be a lot more popular than Apache Beam. While we know about 249 links to AWS Lambda, we've tracked only 14 mentions of Apache Beam. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/9781491983867/. It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.). As for the framework called MapReduce, it isn't used much, but its descendant... - Source: Hacker News / 4 months ago
Apache Beam is one of many tools that you can use. Source: 6 months ago
Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow. - Source: dev.to / over 1 year ago
Apache Beam: Batch/streaming data processing 🔗Link. - Source: dev.to / over 1 year ago
What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all. Source: almost 2 years ago
On this day, we both first learned about Lambda. This was the world's first public Functions-as-a-Service platform, better known as FaaS. They told us that this was the next evolution in Cloud Computing. With Lambda, you could now host snippets of code on AWS. There were no more idle workers, and you could auto-scale with minimal additional configuration required. Also, these snippets were event-driven by nature.... - Source: dev.to / 8 days ago
AWS Lambda simplifies composable applications by offering serverless execution, seamless integration with AWS services, automatic scaling, and cost efficiency without the need to manage servers. - Source: dev.to / 13 days ago
Deploying Dart functions to AWS Lambda enables you to utilize them not only within AWS Lambda but also integrate them with services like Amazon API Gateway, allowing you to leverage them in Flutter applications as well. This unified codebase in Dart offers great convenience. - Source: dev.to / 13 days ago
Event Producers: Generate streams of events, which can be implemented using straightforward microservices with AWS Lambda (for serverless computing), Amazon DynamoDB Streams (to captures changes to DynamoDB tables in real-time), Amazon S3 Event Notifications (Notify when certain events occur in S3 buckets) or AWS Fargate (a serverless compute engine for containers). - Source: dev.to / 21 days ago
Amazon Web Services (AWS) Lambda is a serverless function-as-a-service (FaaS) platform that lets you deploy, run, and scale code in the cloud as self-contained functions without having to manually configure any infrastructure. Lambda runs your functions on demand in response to specific events, such as an HTTP request from the internet or activity in another AWS service. - Source: dev.to / 18 days ago
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Amazon API Gateway - Create, publish, maintain, monitor, and secure APIs at any scale
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.